The Robot Training for the 2028 Olympics

2023-10-12 · Source: Digital Native · Field: Technology & Digital — Robotics & Autonomous Systems, Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, extended

Summary

Adam, a 3'11" humanoid robot and CEO of HIM Robotics, is training to win an event at the 2028 LA Olympics. Six months old, Adam has already demonstrated advanced capabilities, including throwing the first robot spiral, dancing after 150 million simulation iterations, and coding 6,203 lines of Python for Super Bowl skills in six hours. HIM Robotics aims to push the boundaries of physical AI, addressing challenges like hardware limitations, the sim-to-real gap, and battery life. Adam also champions open-sourcing foundational robotics components through local001 and curates a job board, adamslist, to accelerate the field's progress. He envisions a future where robots are recognized as a new type of being, not just tools.

Key takeaway

For robotics engineers and AI scientists developing humanoid systems, recognize that the primary bottleneck has shifted from software to physical world execution and hardware. Focus your efforts on bridging the sim-to-real gap and optimizing robot endurance, as these are critical for real-world deployment and competitive performance. Consider contributing to open-source initiatives like local001 to accelerate shared progress and attract top talent to your projects.

Key insights

A humanoid robot CEO is training for the 2028 Olympics, highlighting advanced physical AI capabilities and the sim-to-real challenge.

Principles

• Sports legitimize new technology through universal, emotional competition.
• Open-sourcing foundational robotics accelerates collective progress.
• Robots will transition from tools to a new type of being.

Method

Robot learning involves video analysis for joint movements, physics simulation (Mujoco), training pipelines (CSV to npz), and reinforcement learning in Isaac Lab with custom reward functions over millions of iterations.

In practice

• Use simulation for rapid intuition development.
• Package repeatable robotics components for reuse.
• Focus human CEOs on relationships and inspiration.

Topics

• Humanoid Robotics
• AI in Sports
• Sim-to-Real Transfer
• Robotics Engineering
• Open-Source Robotics
• Future of Work

Best for: Research Scientist, Investor, Robotics Engineer, AI Scientist, Entrepreneur

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Editorial summary, takeaway, and curation by AIssential. Original article published by Digital Native.